dc_gan.py 文件源码

def __discriminator(self, x, scope, reuse):
        with tf.variable_scope(scope, reuse=reuse):
            x1 = tf.layers.conv2d(x, 64, 5, strides=2, padding='same')
            x1 = LeakyReLU(x1, self.alpha)
            # 16x16x64

            x2 = tf.layers.conv2d(x1, 128, 5, strides=2, padding='same')
            x2 = tf.layers.batch_normalization(x2, training=self.training)
            x2 = LeakyReLU(x2, self.alpha)
            # 8x8x128

            x3 = tf.layers.conv2d(x2, 256, 5, strides=2, padding='same')
            x3 = tf.layers.batch_normalization(x3, training=self.training)
            x3 = LeakyReLU(x3, self.alpha)
            # 4x4x256

            # Flatten it
            flat = tf.reshape(x3, (-1, 4*4*256))
            logits = tf.layers.dense(flat, 1)
            out = tf.sigmoid(logits)

        return out, logits

    #---------------------------------------------------------------------------